Intelligent digital tools for screening of brain connectivity and dementia risk estimation in people affected by mild cognitive impairment.

Risultati finali

User guidelines for clinicians and scientific dissemination

User guidelines for clinicians and scientific dissemination Task 73 M12 60 OUS

Report map of MCI diagnostics and management

Report map of MCI diagnostics and management Task 11 OUS M6

Report on ethics and acceptability of digital diagnostic solutions

Report on ethics and acceptability of digital diagnostic solutions. (Task 1.5, AE, M18)

Clinical study dossier (Clinical study protocol, Informed Consent Form)

Clinical study dossier Clinical study protocol Informed Consent Form Standardised clinical information procedures are approved by the national regulatory authorities from the 4 clinical centres Task 51 IRCCS M9

Standardisation of available and prospective data collection

Standardisation of available and prospective data collection Report on the defined protocol for standardising MEEG NPT and genotyping data collection Task 21 HUH M8

Midterm report on the AI-Mind Predictor versus SOA including report on use of digitalised cognitive tests

Midterm report on the AI-Mind Predictor versus SOA inclusive report on use of digitalised cognitive tests. Report on the comparative analysis on clinical prediction value of the AI-Mind Predictor versus state-of-the-art procedures and Report on comparative analysis of traditional clinical neuropsychological tests and digital version in clinical use for clinical recommen-dations (Task 5.4, IRCCS/OUS, M30)

2 UI/UX Design and Validation Guidelines

UI/UX Design and Validation Guidelines. User personas, scenarios and journey maps; prototypes; use-case stories and guidelines (Task 4.2, TLU, M15)

Decision analytical model for early assessment

Decision analytical model for early assessment. This decision model will be delivered as an interactive dashboard in which parameters of the decision analytical (e.g. expected sensitivity and specificity of new diagnostic tool) could be changed and which shows the impact of the new diagnostic tool on health outcomes of patients and its cost effectiveness. (Task 6.2, RUMC, M18)

Implementation of the central databank

Implementation of the central databank Implementation of a central data storage platform at the TSDSSD server at UiO Task 22 DNV GL M12

AI-Medical Device software compliance requirements map

AIMedical Device software compliance requirements map Task 12 OsloMet M8

Guidelines for data management and sharing (Data Governance Plan)

Guidelines for data management and data sharing Data Governance Plan Task 13 DNV GL M9

Health technology assessment framework for AI-Mind

Health technology assessment framework for AI-Mind. The deliverable will describe a detailed plan for the HTA approach covering all relevant aspects of each HTA domain, including indicators, time frame, tools and collaborations. (Task 6.1, UCSC, M7)

Dissemination and Communication Plan

Dissemination and Communication Plan Task 71 M12 accelCH

AI-Mind data governance and data management protection framework

AIMind data governance and data management protection framework Report describing how the data will be managed and processed to ensure legal compliance including security measures Task 14 DNV GL M12

Midterm report on the AI-Mind Connector specifications

Midterm report on the AI-Mind Connector specifications. Report on the comparative analysis on clinical value of the AI-Mind Connector as a biomarker. (Task 5.3, IRCCS/OUS, M30)

Website establishment and focus group organisation

Website establishment and focus group organisation (Task 7.4, M3, accelCH)

Pubblicazioni

Advancing EEG prediction with deep learning and uncertainty estimation

Autori: Mats Tveter, Thomas Tveitstøl, Christoffer Hatlestad-Hall, Ana S. Pérez T., Erik Taubøll, Anis Yazidi, Hugo L. Hammer, Ira R. J. Hebold Haraldsen
Pubblicato in: Brain Informatics, Numero 11, 2024, ISSN 2198-4018
Editore: Springer Science and Business Media LLC
DOI: 10.1186/s40708-024-00239-6

Health technology assessment framework for artificial intelligence-based technologies

Autori: Rossella Di Bidino, Signe Daugbjerg, Sara C. Papavero, Ira H. Haraldsen, Americo Cicchetti, Dario Sacchini
Pubblicato in: International Journal of Technology Assessment in Health Care, Numero 40, 2024, ISSN 0266-4623
Editore: Cambridge University Press
DOI: 10.1017/s0266462324000308

A systematic literature review of user trust in AI-enabled systems: an HCI perspective

Autori: Amna Khana, Tita Alissa Bach, Harry Hallockb, Gabriela Beltrão, and Sonia Sousa
Pubblicato in: International Journal of Human–Computer Interaction, 2022, ISSN 1044-7318
Editore: Lawrence Erlbaum Associates Inc.
DOI: 10.1080/10447318.2022.2138826

Challenges and Trends in User Trust Discourse in AI Popularity

Autori: Sonia Sousa , José Cravino and Paulo Martins
Pubblicato in: Multimodal Technologies and Interactions, Numero vol 7, 2, 2023, Pagina/e 13, ISSN 2414-4088
Editore: MDPI
DOI: 10.3390/mti7020013

EEG electrodes and where to find them: automated localization from 3D scans

Autori: Mats Tveter, Thomas Tveitstøl, Tønnes Nygaard, Ana S Pérez T, Shrikanth Kulashekhar, Ricardo Bruña, Hugo L Hammer, Christoffer Hatlestad-Hall, Ira R J Hebold Haraldsen
Pubblicato in: Journal of Neural Engineering, Numero 21, 2024, Pagina/e 056022, ISSN 1741-2560
Editore: Institute of Physics Publishing
DOI: 10.1088/1741-2552/ad7c7e

Introducing Region Based Pooling for handling a varied number of EEG channels for deep learning models

Autori: Thomas Tveitstøl, Mats Tveter, Ana S. Pérez T., Christoffer Hatlestad-Hall, Anis Yazisi, Hugo L. Hammer, Ira R. J. Hebold Haraldsen
Pubblicato in: Frontiers in Neuroinformatics, Numero Vol. 17, 2024, ISSN 1662-5196
Editore: Frontiers Research Foundation
DOI: 10.3389/fninf.2023.1272791

Bayesian reduced rank regression models generalizable neural fingerprints that differentiate between individuals in magnetoencephalography data

Autori: Joonas Haakana, Susanne Merz, Samuel Kaski, Hanna Renvall, Riitta Salmelin
Pubblicato in: European Journal of Neuroscience, Numero 59, 2024, Pagina/e 2320-2335, ISSN 0953-816X
Editore: Blackwell Publishing Inc.
DOI: 10.1111/ejn.16292

Intelligent digital tools for screening of brain connectivity and dementia risk estimation in people affected by mild cognitive impairment: The AI-Mind clinical study protocol

Autori: Ira H Haraldsen, Christoffer Hatlestad-Hall, Camillo Marra, Hanna Renvall, Fernando Maestú, Jorge Acosta-Hernández, Soraya Alfonsin, Vebjørn Andersson, Abhilash Anand, Victor Ayllón, Aleksandar Babic, Asma Belhadi, Cindy Birck, Ricardo Bruña, Naike Caraglia, Claudia Carrarini, Erik Christensen, Americo Cicchetti, Signe Daugbjerg, Rossella Di Bidino, Ana Diaz-Ponce, Ainar Drews, Guido Maria Gi
Pubblicato in: Frontiers in Neurorobotics, Numero Vol. 17, 2024, ISSN 1662-5218
Editore: Frontiers Research Foundation
DOI: 10.3389/fnbot.2023.1289406

Early dementia diagnosis, MCI-to-dementia risk prediction, and the role of machine learning methods for feature extraction from integrated biomarkers, in particular for EEG signal analysis.

Autori: Prof. Paolo Maria Rossini, Fabrizio Vecchio, Francesca Miraglia
Pubblicato in: Alzheimer's & Dementia: The Journal of the Alzheimer's Association, Numero vol 18, 12, 2022, Pagina/e 2699-2706, ISSN 1552-5279
Editore: Wiley
DOI: 10.1002/alz.12645

Prognostic Information on Progression to Dementia: Quantification of the Impact on Quality of Life

Autori: Robin Jeanna Vermeulen, Bram Roudijk, Tim Martin Govers, Maroeska Mariet Rovers, Marcel Gerardus Maria Olde Rikkert, Ben Franciscus Martinus Wijnen
Pubblicato in: Journal of Alzheimer’s Disease, Numero 97, 2024, Pagina/e 1829-1840, ISSN 1387-2877
Editore: IOS Press
DOI: 10.3233/jad-231037

User Interface Design for AI-Based Clinical Decision-Support System

Autori: Beltrão, Gabriela; Paramonova, Iuliia; Sousa, Sonia
Pubblicato in: 17th Iberian Conference on Information Systems and Technologies (CISTI), Numero 14, 2022, ISSN 2166-0727
Editore: IEEE
DOI: 10.23919/cisti54924.2022.9820378

Inducing Inductive Bias in Vision Transformer for EEG Classification

Autori: Rabindra Khadka, Pedro G. Lind, Gustavo Mello, Michael A. Riegler, Anis Yazidi
Pubblicato in: ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024, Pagina/e 2096-2100
Editore: IEEE
DOI: 10.1109/icassp48485.2024.10446429

Risultati finali

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